carpeomnia Posted May 18, 2022 Share Posted May 18, 2022 (edited) Hey everyone! Hoping to get an idea of the strength of my application and chances of getting into some of the schools below for a PhD. Left school to work at a management consulting firm which I believe is a bit untraditional. Would also appreciate any school recommendations/adjustments to my current list, any thoughts welcome! Thanks Undergrad Institution: Top 10 University in CanadaMajor(s): Data ScienceGPA: 3.96 (Last 4 Semesters/2 Years), 3.96 (Major), 3.89 (Cumulative) Type of Student: Black International (Canadian) MaleGRE General Test: Taking summer 2022 Programs Applying: Computer Science (PhD), Statistics (PhD), Operation Research (PhD) Research Experience: 2 first-author ACM conference papers (1 applied machine learning and has been cited, 1 data/text mining) 1 last-author conference paper (data/text mining; awarded Best Track Paper in Data Analytics and Big Data) 1 journal publication in geospatial statistics (submitted) Other research in applied machine learning and finance (no publication) Awards/Honors/Recognitions: Gold Medal (graduated with the highest GPA in Major, top of the class) Undergraduate Fulbright Fellowship Letters of Recommendation: One strong letter from an Associate Professor in Statistics & Management Science who I wrote the geospatial statistics paper with (not well-known in CS) One strong letter from an Assistant Professor in Data Science & Business Analytics who I published two papers with in data/text mining (not well-known in CS) One decent/strong letter from an Associate Professor in Economics & Statistics who I performed research with (~1yr together) but no publication One strong letter from a Partner at my management consulting firm (relevant for Operations Research programs) Computer Science Courses: Intro CS I & CS II, Data Structures & Algorithms, Software Tools & Systems, Discrete Structures/Discrete Math, Analysis of Algorithms, Databases I, Data Science IMath/Statistics Courses: Probability & Stats I & II, Statistical Programming, Calc I, Calc II, Intermediate Calc I, Intermediate Calc II, Linear Algebra I, Linear Algebra II, Numerical Analysis, ODEs, Modelling and Simulation, Regression, Generalized Linear Models, Advanced Statistical Computing, Statistical Learning Any Miscellaneous Points that Might Help: Particularly interested in doing research within the field of Machine Learning (and potentially NLP), still figuring this out. Not particularly interested in CV or RL. Would have spent >1 year at a management consulting firm at the time of applying and >2 years by matriculation (a advantage/disadvantage?)Applying to Where: In no particular order here,CMU - PhD in Machine LearningUniversity of Washington - PhD in Computer ScienceColumbia - PhD in Computer ScienceMIT - PhD in EECSPrinceton - PhD in Computer ScienceCornell - PhD in Computer ScienceNYU - PhD in Data ScienceUIUC - PhD in Computer ScienceUT Austin - PhD in Computer ScienceUPenn - PhD in Computer ScienceUC San Diego - PhD in Computer ScienceUCLA- PhD in Computer ScienceGeorgia Tech - PhD in Machine LearningUMichigan - PhD in Computer Science CMU - PhD in StatisticsUniversity of Washington - PhD in StatisticsStanford - PhD in Statistics*Cal Berkeley - PhD in StatisticsUPenn - PhD in StatisticsYale - PhD in Statistics & Data ScienceStanford - PhD in StatisticsCal Berkeley - PhD in StatisticsUPenn - PhD in StatisticsUMichigan - PhD in Statistics CMU - PhD in Operations ResearchMIT - PhD in Operations ResearchGeorgia Tech - PhD in Industrial and Systems EngineeringUMichigan - PhD in Industrial and Operations Engineering Thanks again! Edited May 18, 2022 by carpeomnia Link to comment Share on other sites More sharing options...
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